There was a time when the best salespeople relied on gut feel and innate sales talent to move their products. These days, though, those guessing game methods are increasingly losing out to a new era of science-based sales techniques.
These new techniques leverage analytics and deep client and prospect data, as well as artificial intelligence software, to create powerful business intelligence tools. These tools help sellers derive new levels of insight into how they sell, how sales executives manage and how sales operations are measured.
More Selling, Less Paperwork
The savviest sales leaders have already started to implement this data science-based approach within their sales organizations and are seeing the results. Sales teams are spending less time on administrative tasks and more time selling, new reps are being onboarded faster and more effectively and lead and prospect qualification improvements have led to better sales win rates.
This next generation of sales automation is centered on optimizing salesperson effectiveness by putting their needs first. This approach equips sellers with critical customer data that can help them identify hot spots of opportunity and growth. It puts customers and prospects back at the core of the business by making their needs and wants more clearly understood.
3 Data-Driven Sales Strategies
So how can sales organizations utilize a data-driven approach to drive sales effectiveness? Start by implementing these three strategies:
1. Uncover the top habits of your best salespeople
Start by breaking down all the activities in your sales process such as meetings, phone call and emails. Make capturing and tracking that information easy by centralizing it in a dashboard for each rep and manager.
Then, use those dashboard metrics to compare how your high-performing reps and managers are performing versus their low-performing counterparts. For example, if reps who spend more time interacting with clients in person generate more opportunities and deals, then the sales manager should consider applying that strategy across the entire sales force to increase pipeline and sales. Mapping sales processes out so that this type of workforce intelligence can be applied helps both reps and sales managers identify effective strategies and weed out process inefficiencies.
2. Establish a ‘data picture’ of your perfect prospect
As a starting point, identify who qualifies as your perfect prospect and continue to build that profile out during the sales process by collecting additional information such as age, marital status, Zip code, income level, products owned, title, etc. Creating this profile up front will establish a clear vision for the type of prospect your sales reps should be targeting and will help ensure that they aren’t wasting time chasing bad leads.
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A more general approach that doesn’t require a lot of external or market research is to look at the best customers your company already has and analyze the data on them that’s readily available. What traits do they share? What are their needs? What is their history of engagement with your company?
3. Learn your customers’ preferred pathways for engagement
Sales organizations will want to capture as much information as possible about how their customers are engaging with them across different channels. Are they connecting through your website or did they initiate contact in response to an email marketing campaign? Put in place declarative rules or use machine learning (or both) to assist with customer journey mapping. Create if/then outcome statements to help guide your salespeople in determining what their next actions and best offers should be.
Your salespeople can then decide to use specific offers or actions and the system will capture these activities and learn whether they influenced positive or negative outcomes. By aligning sales strategy with the customer journey, sales organizations can improve win rates by as much as 15 percent and increase the lifetime value of each customer by 26 percent.
Going for the Win-Win
The new science of sales automation borrows heavily from marketing automation, customer analytics and old-school database marketing techniques. But today’s approach to sales automation is also different because it is shifting the paradigm of sales effectiveness from being instinct-driven to insight- and data-driven.
This approach helps sales organizations continue to identify what works and what doesn’t and bring salespeople closer to understanding prospective client needs and wants. As a result, sellers can optimize their sales strategies in real time and empower their reps to be more efficient and effective. In the end, this delivers the best possible offerings for customers and the best outcomes for the company. I call that a win-win.
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